Method and apparatus for processing three-dimensional (3d) pseudoscopic images

ABSTRACT

A method for detecting three-dimensional (3D) pseudoscopic images and a display device for detecting 3D pseudoscopic images are provided. The method includes extracting corresponding feature points in a first view and corresponding feature points in a second view, wherein the first view and the second view form a current 3D image; calculating an average coordinate value of the feature points in the first view and an average coordinate value of the feature points in the second view; based on the average coordinate value of the feature points in the first view and the average coordinate value of the feature points in the second view, determining whether the current 3D image is pseudoscopic or not; and processing the current 3D image when it is determined that the current 3D image is pseudoscopic.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority of Chinese Application No.201510033241.0, filed on Jan. 22, 2015, the entire contents of which arehereby incorporated by reference.

FIELD OF THE INVENTION

The present disclosure generally relates to the field ofthree-dimensional (3D) display technologies and, more particularly,relates to a method for detecting 3D pseudoscopic images and a displaydevice thereof.

BACKGROUND

For a smartphone or a digital camera capable of capturingthree-dimensional (3D) images, it usually takes two images of a samescene, in which the two images have a correct relative order and aparallax between them, and then arranges the two images into a 3D image.In addition, a user may upload two-dimensional (2D) images and utilize a3D image creating software to generate corresponding 3D images of theuploaded2D images. The user may further generate a 3D video based onmultiple 3D video frames (i.e. 3D images), which can be played back on a3D video player.

However, the user may not notice the relative order between the twoimages forming the 3D image or 3D video frame, for example, a left eyeview and a right eye view, and thus may arrange the two images in anincorrect order, resulting an incorrect 3D image. For example, theuser's left eye may see the right eye view and the user's right eye maysee the left eye view, causing 3D image depth to be reversed to theuser. That is, a pseudoscopic image or a pseudoscopic view may begenerated and the viewing experience may be affected.

According to the present disclosure, detection and correction of thepseudoscopic image is of significant importance. If the pseudoscopicimage cannot be detected and corrected, the user experience will besignificantly degraded. To detect whether there is a pseudoscopy betweena left view and a right view may often need to utilize cornersrespectively detected in the left view and the right view.

The disclosed methods and systems are directed to solve one or moreproblems set forth above and other problems.

BRIEF SUMMARY OF THE DISCLOSURE

One aspect of the present disclosure includes a method for detectingthree-dimensional (3D) pseudoscopic images. The method includesextracting corresponding feature points in a first view andcorresponding feature points in a second view, wherein the first viewand the second view form a current 3D image; calculating an averagecoordinate value of the feature points in the first view and an averagecoordinate value of the feature points in the second view; based on theaverage coordinate value of the feature points in the first view and theaverage coordinate value of the feature points in the second view,determining whether the current 3D image is pseudoscopic or not; andprocessing the current 3D image when it is determined that the current3D image is pseudoscopic.

Another aspect of the present disclosure includes a display device fordetecting 3D pseudoscopic images. The display device includes a featureextraction module configured to extract corresponding feature points ina first view and corresponding feature points in a second view, whereinthe first view and the second view form a current 3D image, an averagevalue calculation module configured to calculate an average coordinatevalue of the feature points in the first view and an average coordinatevalue of the feature points in the second view, and a decision moduleconfigured to determine whether the current 3D image is pseudoscopic ornot based on the average coordinate value of the feature points in thefirst view and the average coordinates values of the feature points inthe second view.

Other aspects of the present disclosure can be understood by thoseskilled in the art in light of the description, the claims, and thedrawings of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings are merely examples for illustrative purposesaccording to various disclosed embodiments and are not intended to limitthe scope of the present disclosure.

FIG. 1 illustrates a flow chart of an exemplary method for detecting 3Dpseudoscopic images consistent with disclosed embodiments;

FIG. 2a and FIG. 2b illustrate exemplary feature points in an exemplarymethod for detecting 3D pseudoscopic images consistent with disclosedembodiments;

FIG. 3 illustrates a flow chart of another exemplary method fordetecting 3D pseudoscopic images consistent with disclosed embodiments;

FIG. 4 illustrates a structural schematic diagram of an exemplarydisplay device consistent with disclosed embodiments;

FIG. 5 illustrates a block diagram of an exemplary display deviceconsistent with disclosed embodiments;

FIG. 6 illustrates a structural schematic diagram of another exemplarydisplay device consistent with disclosed embodiments; and

FIG. 7 illustrates an exemplary display device consistent with disclosedembodiments.

DETAILED DESCRIPTION

Reference will now be made in detail to exemplary embodiments of theinvention, which are illustrated in the accompanying drawings.Hereinafter, embodiments consistent with the disclosure will bedescribed with reference to drawings. It is apparent that the describedembodiments are some but not all of the embodiments of the presentinvention. Based on the disclosed embodiments, persons of ordinary skillin the art may derive other embodiments consistent with the presentdisclosure, all of which are within the scope of the present invention.

3D display device is usually based a parallax principle, in which a leftview for a left eye and a right view for a right eye are separated by alens or a grating and then received by the user's left eye and righteye, respectively. The user's brain fuses the left view and the rightview to generate a correct visual perception of 3D display, i.e., a 3Dimage with a correct depth perception.

However, it is possible that the left eye receives the right view whilethe right eye receives the left view, for example, two images with anincorrect relative order are arranged into a 3D image, or two imageswith an incorrect relative position are synthesized into a 3D image,etc. In such cases, the user may experience a pseudoscopic (reversedstereo/3D) image showing an incorrect depth perception. For example, abox on a floor may appear as a box shaped hole in the floor. Thus theviewing experience may be greatly degraded.

The present disclosure provides a method for detecting 3D pseudoscopicimages, which may be implemented into a display device. FIG. 7illustrates an exemplary display device consistent with disclosedembodiments. The display device 700 may be an electronic device which iscapable of capturing 3D images, such as a smartphone, a tablet, and adigital camera, etc., or an electronic device which is capable ofplaying and/or generating 3D images such as a notebook, a TV, and asmartwatch, etc. Although the display device 700 is shown as asmartphone, any device with computing power may be used.

FIG. 5 illustrates a block diagram of an exemplary display deviceconsistent with disclosed embodiments. As shown in FIG. 5, the displaydevice 500 may include a processor 502, a display 504, a camera 506, asystem memory 508, a system bus 510, an input/output module 512, and amass storage device 514. Other components may be added and certaindevices may be removed without departing from the principles of thedisclosed embodiments.

The processor 502 may include any appropriate type of central processingmodule (CPU), graphic processing module (GPU), general purposemicroprocessor, digital signal processor (DSP) or microcontroller, andapplication specific integrated circuit (ASIC). The processor 502 mayexecute sequences of computer program instructions to perform variousprocesses associated with the display device.

The display 504 may be any appropriate type of display, such as plasmadisplay panel (PDP) display, field emission display (FED), cathode raytube (CRT) display, liquid crystal display (LCD), organic light emittingdiode (OLED) display, light emitting diode (LED) display, or other typesof displays.

The camera 506 may be an internal camera in the display device 500 ormay be an external camera connected to the display device 500 over anetwork. The camera 506 may provide images and videos to the displaydevice.

The system memory 508 is just a general term that may include read-onlymemory (ROM), random access memory (RAM) and etc. The ROM may storenecessary software for a system, such as system software. The RAM maystore real-time data, such as images for displaying.

The system bus 510 may provide communication connections, such that thedisplay device may be accessed remotely and/or communicate with othersystems via various communication protocols, such as transmissioncontrol protocol/internet protocol (TCP/IP), hypertext transfer protocol(HTTP), etc.

The input/output module 512 may be provided for users to inputinformation into the display device or for the users to receiveinformation from the display device. For example, the input/outputmodule 512 may include any appropriate input device, such as a remotecontrol, a keyboard, a mouse, an electronic tablet, voice communicationdevices, or any other optical or wireless input devices.

Further, the mass storage device 514 may include any appropriate type ofmass storage medium, such as a CD-ROM, a hard disk, an optical storage,a DVD drive, or other type of storage devices.

During an operating process, the processor 502, executing varioussoftware modules, may perform certain processes to display images orvideos to one or more users.

FIG. 1 illustrates a flow chart of an exemplary method for detecting 3Dpseudoscopic images consistent with disclosed embodiments. As shown inFIG. 1, at the beginning, corresponding feature points in a first viewand corresponding feature points in a second view are extractedrespectively, in which the first view and the second view may form acurrent 3D image (S101).

In particular, the feature points in the first view and the featurepoints in the second view may also be called as interest points,significant points, key points, etc., which may exhibit a certainpattern in a local image, such as intersections of different objects,intersections of different regions with different colors, and points ofdiscontinuity on a boundary of an object, etc.

A display device may extract feature points in the first view and thefeature points in the second view based on Harris corner detectionalgorithm or SUSAN corner detection algorithm, etc. For example, thedisplay device may extract feature parameters of the feature points inthe first view and feature parameters of the feature points in thesecond view, the feature parameters may include a Speeded Up RobustFeatures (SURF), a Scale-invariant feature transform (SIFT) feature, aBinary Robust Invariant Scalable Keypoints (BRISK) feature, and a BinaryRobust Independent Elementary Features (BRIEF), etc.

Based on the feature parameters of the first view and the featureparameters of the second view, the display device may match the featurepoints in the first view and the feature points in the second view, andthen determine the corresponding feature points in the first view andfeature points in the second view.

For example, the feature parameters of the first view and the featureparameters of the second view may be matched based on a K approachingalgorithm. After being determined, the corresponding feature points inthe first view and feature points in the second view may be defined. Forexample, the feature points may be disposed in an X-Y coordinate system,and given an X-axis coordinate value and a Y-axis coordinate value.

After extracting the corresponding feature points in the first view andthe corresponding feature points in the second view, an averagecoordinate value of the feature points in the first view and an averagecoordinate value of the feature points in the second view arecalculated, respectively (S102).

The average coordinate value may be an average of X-axis coordinatevalues of all the feature points in each view (i.e. the first view orthe second view), or an average of Y-axis coordinate values of all thefeature points in each view (i.e. the first view or the second view).

For example, in one embodiment, a left view and a right view may beadopted to form a current 3D image, the left view may be a first viewand the right view may be a second view. An average coordinate value inthe first view may be the sum of X-axis coordinate values of all featurepoints in the first view divided by the number of all the feature pointsin the first view. An average coordinate value in the second view may bethe sum of X-axis coordinate values of all feature points in the secondview divided by the number of all the feature points in the second view.

In one embodiment, an upper view and a lower view may be adopted to forma current 3D image, the upper view may be a first view and the lowerview may be a second view. An average coordinate value in the first viewmay be the sum of Y-axis coordinate values of all feature points in thefirst view divided by the number of all the feature points in the firstview. An average coordinate value in the second view may be the sum ofY-axis coordinate values of all feature points in the second viewdivided by the number of all the feature points in the second view.

Based on the average coordinate value of the feature points in the firstview and the average coordinates value of the feature points in thesecond view, whether the current 3D image is pseudoscopic or not may bedetermined (S103).

In particular, in one embodiment, a left view and a right view may beused to form a current 3D image, and the left view may be a first viewand the right view may be a second view. If an average coordinate valueof feature points in the first view is larger than or equal to anaverage coordinate value of the feature points in the second view, thecurrent 3D image may be determined to be pseudoscopic. On the contrary,if the average coordinate value of the feature points in the first viewis smaller than the average coordinate value of the feature points inthe second view, the current 3D image may be not pseudoscopic.

In another embodiment, a left view and a right view may be used to forma current 3D image, and the right view may be a first view and the leftview may be a second view. If an average coordinate value of featurepoints in the second view is larger than or equal to an averagecoordinate value of feature points in the first view, the current 3Dimage may be determined to be pseudoscopic. On the contrary, if theaverage coordinate value of the feature points in the second view issmaller than the average coordinate value of the feature points in thefirst view, the current 3D image may not be pseudoscopic.

Further, if the current 3D image is determined to be pseudoscopic, thedisplay device may be able to correct the pseudoscopic image throughprocessing the first view and the second.

For example, in one embodiment, a left view and a right view may be usedto form a current 3D image, and the left view may be a first view andthe right view may be a second view. When the current 3D image isdetermined to be pseudoscopic, the display device may correct thepseudoscopic image through adjusting the relative order or the relativeposition of the first view and the second view. That is, the first viewmay become the right view while the second view may become the leftview.

In another embodiment, a left view and a right view may be used to formthe current 3D image, and the right view may be a first view and theleft view may be a second view. When the current 3D image is determinedto be pseudoscopic, the display device may correct the pseudoscopicimage through adjusting the relative order or the relative position ofthe first view and the second view. That is, the first view may becomethe left view while the second view may become the right view.

In another embodiment, an upper view and a lower view may be adopted toform the current 3D image, the upper view may be a first view and thelower view may be a second view. The current 3D image is determined tobe pseudoscopic. The display device may correct the current pseudoscopicimage through adjusting the relative order or the relative position ofthe first view and the second view. That is, the first view may becomethe lower view while the second view may become the upper view.

In another embodiment, an upper view and a lower view may be adopted toform the current 3D image, the lower view may be a first view and theupper view may be a second view. The current 3D image is determined tobe pseudoscopic. The display device may correct the current pseudoscopicimage through adjusting the relative order or the relative position ofthe first view and the second view. That is, the first view may becomethe upper view while the second view may become the lower view.

FIG. 2a and FIG. 2b illustrate exemplary feature points in an exemplarymethod for detecting 3D pseudoscopic views consistent with disclosedembodiments. As shown in FIG. 2a , corners (i.e. features points) aredetected in a first view. Six corners may be detected and coordinatevalues of the six corners in an X-Y coordinate system are L1 (1,2), L2(1,4), L3 (2,5), L4 (3,4), L5 (3,2), L6 (2,1), respectively.

As shown in FIG. 2b , six corners may be detected in a second view andcoordinate values of the six corners in the X-Y coordinate system are R1(2,3), R2 (2,5), R3 (3,6), R4 (4,5), R5 (4,3), R6 (3,2), respectively.The six corners (i.e. feature points) in the first view may correspondto the six corners (i.e. feature points) in the second view. The firstview and the second view may be adopted to form a current 3D image.

An average coordinate value in the first view may be the sum of X-axiscoordinate values of all the feature points in the first view divided bythe number of all the feature points in the first view. That is,A=(2+4+5+4+2+1)/6=3. An average coordinate value in the second view maybe the sum of X-axis coordinate values of all the feature points in thesecond view divided by the number of all the feature points in thesecond view. That is, B=(3+5+6+5+3+2)/6=4.

Because the average coordinate value of the feature points in the firstview is smaller than the average coordinate value of the correspondingfeature points in the second view, the current 3D image may be notpseudoscopic, and a correction may not be required.

If the current 3D image is pseudoscopic, the pseudoscopic image may needto be corrected. In particular, the pseudoscopic image may be correctedthrough adjusting the relative order or relative position of the firstview and the second view when generating the current 3D image ordisplaying the current 3D image. For example, if FIG. 2b shows a firstview and FIG. 2a shows a second view, the relative order of the firstview and the second view may be exchanged to correct the pseudoscopicimage.

Further, a user may utilize a 3D video player implemented in a displaydevice to play a 3D video. However, before playing the 3D video,detecting 3D pseudoscopic images (i.e. the pseudoscopic image detection)in the 3D video may be highly desired, in case the 3D video may includeany pseudoscopic video frames (i.e., pseudoscopic images) which mayaffect the viewing experience. The display device may correct thepseudoscopic video frames as described above, and then play thecorrected 3D video. Thus, 3D video frames may have to be selected beforeextracting the corresponding feature points in the first view and thecorresponding feature points in the second view.

FIG. 3 illustrates a flow chart of another exemplary method fordetecting 3D pseudoscopic images consistent with disclosed embodiments.As shown in FIG. 3, at the beginning, a plurality of3D video frames(i.e. a 3D image) in a 3D video are selected based on a predeterminedrule (S300). Each 3D image may include a first view and a second view.As used in the present disclosure, two views are used to form the 3Dimage. However, any appropriate number of views may be used.

In particular, the predetermined rule, i.e., the selection of the 3Dvideo frames, may be random but not repeated or may be based on acertain interval, which is only for illustrative purposes and is notintended to limit the scope of the present invention. Further, for one3D video, a maximum number of detecting 3D pseudoscopicimages(indicating maximum times of detecting 3D pseudoscopic images) anda minimum number of detecting 3D pseudoscopic images(indicating minimumtimes of detecting pseudoscopic) may be determined. For example, themaximum number of detecting 3D pseudoscopic images may be Q, and theminimum number of detecting 3D pseudoscopic images may be P. Q and P arepositive integers, respectively.

After the plurality of3D video frames (i.e. 3D images) are selected,each3D video frame (i.e. 3D image) may be detected for pseudoscopicimages. For a current 3D video frame (i.e. 3D image) having a first viewand a second view, as shown in FIG. 3, at the beginning, correspondingfeature points in the first view and corresponding feature points in thesecond view forming the current 3D image are extracted, respectively(S301). Then an average coordinate value of the feature points in thefirst view and an average coordinate value of the feature points in thesecond view are calculated respectively (S302). Based on the averagecoordinate value of the feature points in the first view and the averagecoordinates value of the feature points in the second view, whether thecurrent 3D image is pseudoscopic or not may be determined (S303). TheSteps of S301, S302 and S303 may be similar to those of S101, S102 andS103 in FIG. 1, details of which are not repeated here while certaindifferences are explained.

The display device may further record S number of detecting 3Dpseudoscopic images in the 3D video and corresponding detection resultsof the multiple 3D video frames (i.e.

3D images). Then, based on the number S and the corresponding detectionresults of the multiple 3D video frames (i.e., 3D images), the displaydevice may determine whether the 3D video is pseudoscopic or not.

For example, S number of pseudoscopic image detections may be performedin the 3D video, among which N number of 3D video frames (i.e. 3Dimages) may be determined to be pseudoscopic, M number of 3D videoframes (i.e. 3D images) may be determined to be not pseudoscopic and Tnumber of pseudoscopic image detections may be failed. In particular,S=M+N+T, S, M, N and T are positive integers respectively. P denotes theminimum number of detecting 3D pseudoscopic images in the 3D video, P isa positive integer.

If the value of M/S is larger than a predetermined threshold value, the3D video may not be determined to be pseudoscopic. If the value of N/Sis larger than a predetermined threshold value, the 3D video may bedetermined to be pseudoscopic. The predetermined threshold value may bedetermined according to requirements of 3D viewing experience. Variousrequirements may have various threshold values.

For example, according to certain requirements of 3D viewing experience,the predetermined threshold value may be set as approximately 0.7. Thatis, if a condition of S>=P and (M/S)>0.7 is satisfied, the 3D video maynot be determined to be pseudoscopic and the pseudoscopic imagedetection in the 3D video may end. If the condition of S>=P and(M/S)>0.7 is not satisfied, the pseudoscopic image detection in the 3Dvideo may have to continue.

If a condition of S>=P and (N/S)>0.7 is satisfied, the 3D video may bedetermined to be pseudoscopic and the pseudoscopic image detection inthe 3D video may end. If the condition of S>=P and (N/S)>0.7 is notsatisfied, the pseudoscopic image detection in the 3D video may have tocontinue.

If S>Q, the pseudoscopic image detection in the 3D video may bedetermined to be failed and the pseudoscopic image detection in the 3Dvideo may end, otherwise the pseudoscopic image detection in the 3Dvideo may have to continue. Q denotes the maximum number of thedetecting 3D pseudoscopic images in the 3D video, and P denotes theminimum number of detecting 3D pseudoscopic images in the 3D video. Inparticular, Q>P, a preferred value of P may be 5 and a preferred valueof Q may be 10.

If the 3D video is determined to be pseudoscopic, the pseudoscopic videoframes (i.e., pseudoscopic image) in the 3D video may need to becorrected through adjusting the relative order or relative position ofthe first view and the second view in the pseudoscopic video frames(i.e., pseudoscopic image), respectively.

Through respectively calculating the average coordinate value of thefeature points in the first view and the average coordinate value of thefeature points in the second view, the display device may be able todetermine whether the current 3D image is pseudoscopic or not. Further,based on the results of the pseudoscopic image detection, the displaydevice may determine whether the relative order of the relative positionof the first view and the second view forming the current 3D image needsto be changed. Thus, the display device may enable the user to watch 3Dimages/3D videos with correct depth perceptions, and enhance the viewingexperience.

FIG. 4 illustrates a structural schematic diagram of an exemplarydisplay device consistent with disclosed embodiments. The display device400 may be an electronic device which is capable of capturing 3D images,such as a smartphone, a tablet, and a digital camera, etc., or anelectronic device which is capable of playing and/or generating 3Dimages such as a notebook, a TV, and a smartwatch, etc. (e.g., FIG. 7)

As shown in FIG. 4, the display device 400 may include a featureextraction module 401, an average value calculation module 402 and adecision module 403. All of the modules may be implemented in hardware,software, or a combination of hardware and software. Software programsmay be stored in the system memory 508, which may be called and executedby the processor 502 to complete corresponding functions/steps.

The feature extraction module 401 may be configured to extractcorresponding feature points in a first view and in a second view, inwhich the first view and the second view may form a current 3D image.The average value calculation module 402 may be configured to calculatean average coordinate value of the feature points in the first view andan average coordinate value of the feature points in the second view.Based on the average coordinate value of the feature points in the firstview and the average coordinates values of the feature points in thesecond view, the decision module 403 may be configured to determinewhether the current 3D image is pseudoscopic or not.

For example, in one embodiment, a left view and a right view may beadopted to form a current 3D image, a first view may be the left viewand a second view may be the right view. If an average coordinate valueof feature points in the first view is larger than or equal to anaverage coordinate value of feature points in the second view, thedecision module 403 may determine the current 3D image to bepseudoscopic.

In particular, the average coordinate value of the feature points in thefirst view may be the sum of all X-axis coordinate values of all thefeature points in the first view divided by the number of all thefeature points in the first view. The average coordinate value of thefeature points in the second view may be the sum of all X-axiscoordinate values of all the feature points in the second view dividedby the number of all the feature points in second first view.

In another embodiment, a left view and a right view may be adopted toform a current 3D image, a first view may be the right view and a secondview may be the left view. If an average coordinate value of featurepoints in the second view is larger than or equal to an averagecoordinate value of feature points in the first view, the decisionmodule 403 may determine that the current 3D image to be pseudoscopic.

In particular, the average coordinate value of the feature points in thefirst view may be the sum of all X-axis coordinate values of all thefeature points in the first view divided by the number of all thefeature points in the first view. The average coordinate value of thefeature points in the second view may be the sum of all X-axiscoordinate values of all the feature points in the second view dividedby the number of all the feature points in second first view.

FIG. 6 illustrates a structural schematic diagram of another exemplarydisplay device consistent with disclosed embodiments. As shown in FIG.6, the display device 600 may include a feature extraction module 601,an average value calculation module 602 and a decision module 603, whichmay perform similar functions as the modules in FIG. 4. The similaritiesbetween FIG. 4 and FIG. 6 are not repeated here, while certaindifferences are explained.

The display device 600 may further include a pseudoscopic imageprocessing module 604. If the current 3D image is pseudoscopic, thepseudoscopic image processing module may be configured to correct thepseudoscopic image through processing the first view and the second viewforming the current 3D image. In particular, the pseudoscopic imageprocessing module may adjust the relative order or relative position ofthe first view and the second view.

The display device 600 may also include a selecting module 605configured to select 3D video frames (i.e., 3D images) in a 3D videobased on a predetermined rule. Each 3D video frame (i.e., 3D image) mayinclude a first view and a second view.

The display device 600 may also include a recording module 606configured to record the number of detecting 3D pseudoscopic images inthe 3D video (i.e. times of detecting 3D pseudoscopic images in the 3Dvideo) and corresponding detection results of detecting 3D pseudoscopicimages in the 3D video. Based on the number of detecting 3D pseudoscopicimages in the 3D video and the corresponding detection results ofdetecting 3D pseudoscopic images in the 3D video, the decision module603 may determine whether the 3D video is pseudoscopic or not. If the 3Dvideo is determined to be pseudoscopic, the pseudoscopic imageprocessing module may adjust the relative order or relative position ofthe first view and the second view in the pseudoscopic video frames(i.e. pseudoscopic image) in the 3D video, respectively.

The display device consistent with disclosed embodiments may be anelectronic device implemented with various software modules of detecting3D pseudoscopic images consistent with disclosed embodiments, in whichthe details of detecting 3D pseudoscopic images may be referred to theprevious description of detecting 3D pseudoscopic images. It should benoted that, names of the software modules are only for illustrativepurposes, which are not intended to limit the scope of the presentinvention.

The method for detecting 3D pseudoscopic images may be used inapplications such as capturing 3D images and playing 3D videos. For asmartphone or a digital camera capable of capturing 3D images, itusually takes two images of a same scene, in which the two images have acorrect relative order and a parallax between them, and then arrangesthe two images into a 3D image. In addition, a user may upload 2D imagesand utilize a 3D image creating software to generate corresponding 3Dimages of the uploaded 2D images. The user may further generate a 3Dvideo based on multiple 3D video frames (i.e., 3D images), which can beplayed back on a video player.

However, the user may not notice the relative order between the twoimages forming the 3D image or 3D video frame, and thus may arrange thetwo images in an incorrect order, resulting an incorrect 3D image. Thatis, a pseudoscopic image or a pseudoscopic view may be generated and theviewing experience may be affected.

Through respectively calculating the average coordinate value of thefeature points in the first view and the average coordinate value of thefeature points in the second view, the display device may be able todetermine whether the current 3D image is pseudoscopic or not. Further,based on the results of the pseudoscopic image detection, the displaydevice may determine whether the relative order of the relative positionof the first view and the second view forming the current 3D image needsto be changed. Thus, the display device may enable the user to watch 3Dimages/3D videos with correct depth perceptions, and enhance the viewingexperience.

Those of skill would further appreciate that the various illustrativemodules and algorithm steps disclosed in the embodiments may beimplemented as electronic hardware, computer software, or combinationsof both. To clearly illustrate this interchangeability of hardware andsoftware, various illustrative modules and steps have been describedabove generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present invention.

The steps of a method or algorithm disclosed in the embodiments may beembodied directly in hardware, in a software module executed by aprocessor, or in a combination of the two. A software module may residein RAM, flash memory, ROM, EPROM (erasable programmable read-onlymemory), EEPROM (electrically erasable programmable read-only memory),registers, hard disk, a removable disk, a CD-ROM, or any other form ofstorage medium known in the art.

The description of the disclosed embodiments is provided to illustratethe present invention to those skilled in the art. Various modificationsto these embodiments will be readily apparent to those skilled in theart, and the generic principles defined herein may be applied to otherembodiments without departing from the spirit or scope of the invention.Thus, the present invention is not intended to be limited to theembodiments shown herein but is to be accorded the widest scopeconsistent with the principles and novel features disclosed herein.

What is claimed is:
 1. A method for detecting 3D pseudoscopic images,comprising: extracting corresponding feature points in a first view andcorresponding feature points in a second view, wherein the first viewand the second view form a current 3D image; calculating an averagecoordinate value of the feature points in the first view and an averagecoordinate value of the feature points in the second view; based on theaverage coordinate value of the feature points in the first view and theaverage coordinate value of the feature points in the second view,determining whether the current 3D image is pseudoscopic or not; andprocessing the current 3D image when it is determined that the current3D image is pseudoscopic.
 2. The method for detecting 3D pseudoscopicimages according to claim 1, wherein: the average coordinate value ofthe feature points in the first view is an average of X-axis coordinatevalues of the feature points in the first view; and the averagecoordinate value of the feature points in the second view is an averageof X-axis coordinate values of the feature points in the second view. 3.The method for detecting 3D pseudoscopic images according to claim 1,wherein determining whether the current 3D image is pseudoscopic or notfurther includes: determining that the current 3D image is pseudoscopicwhen the average coordinate value of the feature points in the firstview is larger than or equal to the average coordinate value of thefeature points in the second view, wherein the first view is a left viewand the second view is a right view.
 4. The method for detecting 3Dpseudoscopic images according to claim 1, wherein determining whetherthe current 3D image is pseudoscopic or not further includes:determining that the current 3D image is pseudoscopic when the averagecoordinate value of the feature points in the second view is larger thanor equal to the average coordinate value of the feature points in thefirst view, wherein the first view is a right view and the second viewis a left view.
 5. The method for detecting 3D pseudoscopic imagesaccording to claim 1, wherein processing the current 3D image furtherincludes: adjusting the first view and the second view forming thecurrent 3D image when it is determined that the current 3D image ispseudoscopic, such that pseudoscopy in the current 3D image iscorrected.
 6. The method for detecting 3D pseudoscopic images accordingto claim 5, wherein adjusting the first view and the second view whenthe current 3D image is pseudoscopic further includes: changing arelative order of the first view and the second view forming the current3D image.
 7. The method for detecting 3D pseudoscopic images accordingto claim 1, further including: selecting a plurality of 3D video framesfrom a 3D video based on a predetermined rule, wherein each 3D videoframe is a 3D image having a first view and a second view, beforeextracting corresponding feature points in the first view andcorresponding feature points in the second view.
 8. The method fordetecting 3D pseudoscopic images according to claim 7, furtherincluding: Recording detection results of detecting 3D pseudoscopicimages in each of the plurality of 3D video frames; and Recording anumber of times of detecting 3D pseudoscopic images in the 3D video. 9.The method for detecting 3D pseudoscopic images according to claim 8,further including: based on the number of times of detecting 3Dpseudoscopic images in the 3D video and the detection results ofdetecting 3D pseudoscopic images in each of the plurality of 3D videoframes, determining whether the 3D video is pseudoscopic or not.
 10. Themethod for detecting 3D pseudoscopic images according to claim 9,further including: when the 3D video is determined as pseudoscopic,respectively changing a relative order of the first view and the secondview in each3D video frame which is pseudoscopic.
 11. A display devicefor detecting 3D pseudoscopic images, comprising: a feature extractionmodule configured to extract corresponding feature points in a firstview and corresponding feature points in a second view, wherein thefirst view and the second view form a current 3D image; an average valuecalculation module configured to calculate an average coordinate valueof the feature points in the first view and an average coordinate valueof the feature points in the second view; and a decision moduleconfigured to determine whether the current 3D image is pseudoscopic ornot based on the average coordinate value of the feature points in thefirst view and the average coordinates values of the feature points inthe second view.
 12. The display device according to claim 11, wherein:the average coordinate value of the feature points in the first view isan average of X-axis coordinate values of the feature points in thefirst view; and the average coordinate value of the feature points inthe second view is an average of X-axis coordinate values of the featurepoints in the second view.
 13. The display device according to claim 11,wherein the decision module is further configured to: determine that thecurrent 3D image is pseudoscopic when the average coordinate value ofthe feature points in the first view is larger than or equal to theaverage coordinate value of the feature points in the second view,wherein the first view is a left view and the second view is a rightview.
 14. The display device according to claim 11, wherein the decisionmodule is further configured to: determine that the current 3D image ispseudoscopic when the average coordinate value of the feature points inthe second view is larger than or equal to the average coordinate valueof the feature points in the first view, wherein the first view is aright view and the second view is a left view.
 15. The display deviceaccording to claim 11, further including: a pseudoscopic imageprocessing module configured to adjust the first view and the secondview forming the current 3D image when the decision module determinesthat the current 3D image is pseudoscopic, such that pseudoscopy in thecurrent 3D image is corrected.
 16. The display device according to claim15, wherein pseudoscopic image processing module is further configuredto: change a relative order of the first view and the second viewforming the current 3D image.
 17. The display device according to claim11, further including: a selecting module configured to select aplurality of 3D video frames from a 3D video based on a predeterminedrule, wherein each 3D video frame is a 3D image having a first view anda second view.
 18. The display device according to claim 11, furtherincluding: a recording module configured to record a number of times ofdetecting 3D pseudoscopic images in the 3D video and detection resultsof detecting 3D pseudoscopic images in each of the plurality of 3D videoframes.
 19. The display device according to claim 18, wherein thedecision module is further configured to: based on the number of timesof detecting 3D pseudoscopic images in the 3D video and the detectionresults of detecting 3D pseudoscopic images in each of the plurality of3D video frames, determine whether the 3D video is pseudoscopic or not.20. The display device according to claim 19, wherein the pseudoscopicimage processing module is further configured to: when the decisionmodule determines the 3D video is pseudoscopic, respectively change arelative order of the first view and the second view in each3D videoframe which is pseudoscopic.